Parallel programming tools are limited, making effective parallel programming difficult and
cumbersome. Compilers that translate conventional sequential programs into parallel form …

Speeding up sequential programs on multicores is a challenging problem that is in urgent
need of a solution. Automatic parallelization of irregular pointer-intensive codes, exemplified …

We present a novel Hybrid Analysis technology which can efficiently and seamlessly
integrate all static and run-time analysis of memory references into a single framework that is …

Many important applications, such as those using sparse data structures, have memory
reference patterns that are unknown at compile-time. Prior work has developed run-time …

Compiler-based auto-parallelization is a much-studied area but has yet to find widespread
application. This is largely due to the poor identification and exploitation of application …

This paper presents the results of the Cedar Hand-Parallelization Experiment conducted
from 1989 through 1992, within the Center for Supercomputing Research and Development …

We present QuickStep, a novel system for parallelizing sequential programs. Unlike
standard parallelizing compilers (which are designed to preserve the semantics of the …

This paper presents a compiler and runtime framework for parallelizing sparse matrix
computations that have loop-carried dependences. Our approach automatically generates a …

As increasing the performance of single-threaded processors becomes increasingly difficult,
consumer desktop processors are moving toward multi-core designs. One way to enhance …

Dependence between iterations in sparse computations causes inefficient use of memory
and computation resources. This paper proposes sparse fusion, a technique that generates …